Tracking global patterns of N-linked glycosylation site variation in highly variable viral glycoproteins: HIV, SIV, and HCV envelopes and influenza hemagglutinin

Abstract

Human and simian immunodeficiency viruses (HIV and SIV), influenza virus, and hepatitis C virus (HCV) have heavily glycosylated, highly variable surface proteins. Here we explore N-linked glycosylation site (sequon) variation at the population level in these viruses, using a new Web-based program developed to facilitate the sequon tracking and to define patterns (www.hiv.lanl.gov). This tool allowed rapid visualization of the two distinctive patterns of sequon variation found in HIV-1, HIV-2, and SIV CPZ. The first pattern (fixed) describes readily aligned sites that are either simply present or absent. These sites tend to be occupied by high-mannose glycans. The second pattern (shifting) refers to sites embedded in regions of extreme local length variation and is characterized by shifts in terms of the relative position and local density of sequons; these sites tend to be populated by complex carbohydrates. HIV, with its extreme variation in number and precise location of sequons, does not have a net increase in the number of sites over time at the population level. Primate lentiviral lineages have host species-dependent levels of sequon shifting, with HIV-1 in humans the most extreme. HCV E1 and E2 proteins, despite evolving extremely rapidly through point mutation, show limited sequon variation, although two shifting sites were identified. Human influenza A hemagglutinin H3 HA1 is accumulating sequons over time, but this trend is not evident in any other avian or human influenza A serotypes.

The Genetic Bottleneck in Vertical Transmission of Subtype C HIV-1 Is Not Driven by Selection of Especially Neutralization-Resistant Virus from the Maternal Viral Population

“…Sequences were translated by using the Translate program (www.hiv.lanl.gov) and aligned with MAFFT version 5.8 using the L-INS-i method (23); putative glycosylation sites were identified by using the N-Glycosite tool (61). The fraction of maternal sequences with each glycosylation site was subtracted from the fraction of infant sequences with that same site to calculate the fractional difference between mothers and infants.…”

“…We next analyzed the number of encoded PNG sites in each sequence, as identified using the N-Glycosite program (61). Using the GEE model, we found the mean number of PNG sites in V1-V5 in IP infant env sequences was significantly less than matched maternal env sequences (P ϭ 0.012), and the effect was most pronounced in V1-V2 (P ϭ 0.006).…”

Hippophae rhamnoides N-glycoproteome analysis: a small step towards sea buckthorn proteome mining

“…Sub-cellular localization was predicted using Plant-mPLoC tool (http://www.csbio.sjtu. edu.cn/bioinf/plant-multi/; Chou and Shen 2010) and N-glycosylation sites were predicted using N-GLYCOSITE tool (http://www.hiv.lanl.gov/content/ sequence/GLYCOSITE/glycosite.html; Zhang et al 2004). GO (Gene Ontology) annotation was performed using BLAST2GO.…”

Hepatitis C databases, principles and utility to researchers

“…-Glycosite tallies, plots and compares N-links glycosylation sites in a protein. 15 -Entropy calculates and plots the variability of each position in an alignment. 16 The variability is calculated as an entropy score.…”

“…The Los Alamos Databases Using only database resources, a recent paper discussed the distribution of glycosylation sites in HCV and HIV. 15 Authors from UCSD introduced a simplified model to describe substitution rate distributions, using data from the Los Alamos se-quence database as an illustration. 26 Two studies by the group of Peter Simmonds in Edinburgh relied partly on the Los Alamos database: one analyzing RNA secondary structures in the HCV Core and NS5B genes, 27 the other reviewing current knowledge about HCV evolution.…”